• Geotechnical Engineering
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• v.9 no.3
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• pp.61-66
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• 1993

In this paper, the incorporation of qualitative(or soft) data, such as outputs of geophysical tests or construction experience which has so far been cumulated, was discussed for rock classsification. Geostatistics wart used for this research since the parameters for the design of tunnels are spatially correlated. In particular, indicator kriging technique, which is one of non -parametric approaches, was used. As a selection criteria for an optimal classification, the cost of errors was adopted and the binary classes were only considered for rock classification. In future, incorporating an appreciable amount of available qualitative data will be necessary in tunnelling projects in which quantitative data are scarce. In this respect, this research is of great significance.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.319-326
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• 2003

In site investigation for tunnel designs, nowadays, geophysical exploration such as seismic exploration and electric resistivity exploration as well as drilling logging is frequently carried out. A method which can systematically make the utmost use of all available data obtained from investigation, therefore, is strongly required for the optimal evaluation of ground conditions in terms of rock mass class, etc. Many researchers have proposed using qualitative data to cope with the lack of quantitative data. In this study, an evaluation technique of rock mass classes in undrilled region was proposed based upon multiple indicator kriging method which is a geostatistical technique. It was shown that two types of data with different degree of uncertainty, for example, drilling logging data and geophysical exploration data, could be simultaneously utilized in evaluating rock mass classes for a real tunnel design.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.140-143
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• 2003

Air permeabilities in unsaturated fractured tuff at the Apache Leap Research Site (ALRS) near Superior, Arizona, exhibit a self-affine behavior, thus renders a field random fractal. Based up fractal scaling, the observed scale effect has been interpreted [Hyun et al., 2002]. Recently, Frantziskonis and Hansen [2000] presented that fractal scaling can be represented based on wavelets. This study deals with the way of using wavelets for fractal scaling. A numerical study is presented to examine the applicability of wavelet-based approach to determining upscaled air permeability values on various data supports at the site. To characterize the scaling property of self-affine fields generated based upon wavelets, Hurst coefficient, H. was inferred by applying the average wavelet coefficient (AWC) method. The result yielded H = 0.24, which is very close to the result of geostatistical analysis using a power variogram (H = 0.22). The study concludes that wavelet-based scaling is a useful way of determining parameter values on different data supports, which is an essential task for modeling of subsurface flow and mass transport in a numeric grid with different resolutions (grid size).

• Water for future
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• v.17 no.4
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• pp.303-310
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• 1984

One of the delicate problems in aquifer problems in aquifer management is the identification of the spatial distribution of the hydrological parameters. To determine the distribution of the transmissivity in a aquifer, several data are available; the local values of transmissivity around well, interference tests, some knowledge of geological structure. All this information has to be combined to find a plausible representation of the aquifer. According to a three phased optimization process calculation is carried out; geostatistical estimate of the parameter field on the basis of known well point values adjustable on a limited numerical model, and modification of the values ot pilot points by a minimization algorithm. This procedure, applied to a known case, has proved to be very useful.

• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.933-944
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• 2010

This study compares the CEM and SGS methods which are geostatistical stochastic simulation methods for assessing the uncertainty by spatial variability in the estimation of the spatial distribution of probability rainfall. In the stochastic simulations using CEM and SGS, two methods show almost similar results for the reproduction of spatial correlation structure, the statistics (standard deviation, coefficient of variation, interquartile range, and range) of realizations as uncertainty measures, and the uncertainty distribution of basin mean rainfall. However, the CEM is superior to SGS in aspect of simulation efficiency.

• Geotechnical Engineering
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• v.11 no.2
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• pp.71-78
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• 1995

In this paper, a study was performed on classifying a rock mass into multiple classes as in rock mass classification systems, such as RMR system and Q system etc. In a situation with only limited quantitative data available, it was sought to employ a way of incorporating qualitative data in a systematical and reasonable manner. It is based on the realm of Geostatistics. In particular, indicator kriging technique, which is one of non-parametric approaches, was used. As a selection criterion for an optimal classification, the cost of errors was adopted. As a result, the binary rock classification method developed before was extended and generalized for multiple rock classification with its total number of classes unlimited.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.143-152
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• 2003

This paper suggests the improvement of the Sumjinkang for the estimation of areal averages of heavy rainfall events based on the optimal network and three existing networks. The problem consists of minimizing an objective function which includes both the accuracy of the areal mean estimation as expressed by the Kriging variance and the economic cost of the data collection. The wellknown geostatistical variance-reduction method is used in combination with SATS which is an algorithm of minimization. At the first stage, two kinds of optimal solutions are obtained by two trade-off coefficients. One of them is a optimal solution, the other is an alternative. At the second stage, a quasi optimal network and a quasi alternative are suggested so that the existing raingages near to the selected optimal raingages are included in the two solutions instead of gages of new gages.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.525-532
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• 2010

Kriging is widely applied to dealing with the spatial distribution of rainfall, however its prediction results are different according to the selection of variogram type. This study investigated adequate variogram for daily rainfall. The comparative results show that kriging prediction with covariates is better than that without covariates. The Mat$\acute{e}$rn correlation function, which is the most general type variogram, is recommended if adequate variogram is difficult to determine.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.475-487
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• 2024

Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

• Journal of the Korean Geographical Society
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• v.44 no.2
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• pp.105-121
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• 2009

The accurate official map of air temperature does not exist for the Hawaiian Islands due to the limited number of weather stations on the rugged volcanic landscape. To alleviate the major problem of temperature mapping, satellite-measured land surface temperature (LST) data were used as an additional source of sample points. The Moderate Resolution Imaging Spectroradiometer (MODIS) system provides hypertemperal LST data, and LST pixel values that were frequently observed (${\ge}$14 days during a 32-day composite period) had a strong, consistent correlation with air temperature. Systematic grid points with a spacing of 5km, 10km, and 20km were generated, and LST-derived air temperature estimates were extracted for each of the grid points and used as input to inverse distance weighted (IDW) and cokriging methods. Combining temperature data and digital elevation model (DEM), cokriging significantly improved interpolation accuracy compared to IDW. Although a cokriging method is useful when a primary variable is cross-correlated with elevation, interpolation accuracy was sensitively influenced by the seasonal variations of weather conditions. Since the spatial variations of local air temperature are more variable in the wet season than in the dry season, prediction errors were larger during the wet season than the dry season.